IDEAS home Printed from https://ideas.repec.org/a/spr/telsys/v77y2021i3d10.1007_s11235-021-00773-2.html
   My bibliography  Save this article

Benchmarking of AQM methods of network congestion control based on extension of interval type-2 trapezoidal fuzzy decision by opinion score method

Author

Listed:
  • Mahmood M. Salih

    (Universiti Pendidikan Sultan Idris
    Tikrit University)

  • O. S. Albahri

    (Universiti Pendidikan Sultan Idris)

  • A. A. Zaidan

    (Universiti Pendidikan Sultan Idris
    Sultan Azlan Shah Campus, Universiti Pendidikan Sultan Idris)

  • B. B. Zaidan

    (Universiti Pendidikan Sultan Idris
    Sultan Azlan Shah Campus, Universiti Pendidikan Sultan Idris
    Future Technology Research Center, National Yunlin University of Science and Technology)

  • F. M. Jumaah

    (Universiti Pendidikan Sultan Idris)

  • A. S. Albahri

    (Universiti Pendidikan Sultan Idris
    Informatics Institute for Postgraduate Studies (IIPS), Iraqi Commission for Computers and Informatics (ICCI))

Abstract

This study presents a benchmarking and evaluation approach for active queue management (AQM) network congestion control methods, which are considered as a problem of multi-criteria decision-making (MCDM). In recent years, the development of MCDM methods has been studied from various perspectives. The latest one called fuzzy decision by opinion score method (FDOSM) has proved its efficiency in solving the concerns faced by other methods. However, the approach of FDOSM and its extension is based on fuzzy type-1, which suffers from issues, especially minimising the effect of data uncertainties. Therefore, this study extended FDOSM into a fuzzy type-2 environment that utilises interval type-2 trapezoidal (IT2T) membership, and then discusses the effectiveness of such membership on AQM method benchmarking. The methodology of this study involves two consecutive phases. The first phase is the construction of a decision matrix utilised in AQM method benchmarking based on a list of AQM methods and multiple evaluation criteria. The second phase is regarding the new method (IT2T-FDOSM), which illustrated two main stages, namely, data transformation unit and data processing. The findings of this study are the following: (1) Individual results of benchmarking which used six decision-makers are almost similar, with the AQM fuzzy GRED method ranked as the best. (2) The group benchmarking results show that a relatively similar order and fuzzy GRED method is the best as well. (3) IT2T-FDOSM can deal with the uncertainty problem properly. (4) The results show significant differences amongst the groups’ scores, which indicate the validity of the IT2T-FDOSM results.

Suggested Citation

  • Mahmood M. Salih & O. S. Albahri & A. A. Zaidan & B. B. Zaidan & F. M. Jumaah & A. S. Albahri, 2021. "Benchmarking of AQM methods of network congestion control based on extension of interval type-2 trapezoidal fuzzy decision by opinion score method," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 77(3), pages 493-522, July.
    • Handle: RePEc:spr:telsys:v:77:y:2021:i:3:d:10.1007_s11235-021-00773-2
    DOI: 10.1007/s11235-021-00773-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11235-021-00773-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11235-021-00773-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. O. H. Salman & A. A. Zaidan & B. B. Zaidan & Naserkalid & M. Hashim, 2017. "Novel Methodology for Triage and Prioritizing Using “Big Data” Patients with Chronic Heart Diseases Through Telemedicine Environmental," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(05), pages 1211-1245, September.
    2. R. T. Mohammed & R. Yaakob & A. A. Zaidan & N. M. Sharef & R. H. Abdullah & B. B. Zaidan & K. A. Dawood, 2020. "Review of the Research Landscape of Multi-Criteria Evaluation and Benchmarking Processes for Many-Objective Optimization Methods: Coherent Taxonomy, Challenges and Recommended Solution," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 19(06), pages 1619-1693, November.
    3. Pei, Lijun & Wu, Fanxin, 2021. "Periodic solutions, chaos and bi-stability in the state-dependent delayed homogeneous Additive Increase and Multiplicative Decrease/Random Early Detection congestion control systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 182(C), pages 871-887.
    4. F. M. Jumaah & A. A. Zaidan & B. B. Zaidan & R. Bahbibi & M. Y. Qahtan & A. Sali, 2018. "Technique for order performance by similarity to ideal solution for solving complex situations in multi-criteria optimization of the tracking channels of GPS baseband telecommunication receivers," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 68(3), pages 425-443, July.
    5. Maimuna Khatari & A. A. Zaidan & B. B. Zaidan & O. S. Albahri & M. A. Alsalem, 2019. "Multi-Criteria Evaluation and Benchmarking for Active Queue Management Methods: Open Issues, Challenges and Recommended Pathway Solutions," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(04), pages 1187-1242, July.
    6. Mohammed Talal & A. A. Zaidan & B. B. Zaidan & O. S. Albahri & M. A. Alsalem & A. S. Albahri & A. H. Alamoodi & M. L. M. Kiah & F. M. Jumaah & Mussab Alaa, 2019. "Comprehensive review and analysis of anti-malware apps for smartphones," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 72(2), pages 285-337, October.
    7. Karrar Hameed Abdulkareem & Nureize Arbaiy & A. A. Zaidan & B. B. Zaidan & O. S. Albahri & M. A. Alsalem & Mahmood M. Salih, 2020. "A Novel Multi-Perspective Benchmarking Framework for Selecting Image Dehazing Intelligent Algorithms Based on BWM and Group VIKOR Techniques," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 19(03), pages 909-957, May.
    8. A. A. Zaidan & B. B. Zaidan & M. A. Alsalem & Fayiz Momani & Omar Zughoul, 2020. "Novel Multiperspective Hiring Framework for the Selection of Software Programmer Applicants Based on AHP and Group TOPSIS Techniques," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 19(03), pages 775-847, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Albahri, A.S. & Alnoor, Alhamzah & Zaidan, A.A. & Albahri, O.S. & Hameed, Hamsa & Zaidan, B.B. & Peh, S.S. & Zain, A.B. & Siraj, S.B. & Alamoodi, A.H. & Yass, A.A., 2021. "Based on the multi-assessment model: Towards a new context of combining the artificial neural network and structural equation modelling: A review," Chaos, Solitons & Fractals, Elsevier, vol. 153(P1).
    2. Noor S. Baqer & A. S. Albahri & Hussein A. Mohammed & A. A. Zaidan & Rula A. Amjed & Abbas M. Al-Bakry & O. S. Albahri & H. A. Alsattar & Alhamzah Alnoor & A. H. Alamoodi & B. B. Zaidan & R. Q. Malik , 2022. "Indoor air quality pollutants predicting approach using unified labelling process-based multi-criteria decision making and machine learning techniques," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 81(4), pages 591-613, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Albahri, A.S. & Alnoor, Alhamzah & Zaidan, A.A. & Albahri, O.S. & Hameed, Hamsa & Zaidan, B.B. & Peh, S.S. & Zain, A.B. & Siraj, S.B. & Alamoodi, A.H. & Yass, A.A., 2021. "Based on the multi-assessment model: Towards a new context of combining the artificial neural network and structural equation modelling: A review," Chaos, Solitons & Fractals, Elsevier, vol. 153(P1).
    2. Noor S. Baqer & A. S. Albahri & Hussein A. Mohammed & A. A. Zaidan & Rula A. Amjed & Abbas M. Al-Bakry & O. S. Albahri & H. A. Alsattar & Alhamzah Alnoor & A. H. Alamoodi & B. B. Zaidan & R. Q. Malik , 2022. "Indoor air quality pollutants predicting approach using unified labelling process-based multi-criteria decision making and machine learning techniques," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 81(4), pages 591-613, December.
    3. Fabián Silva-Aravena & Hugo Núñez Delafuente & César A. Astudillo, 2022. "A Novel Strategy to Classify Chronic Patients at Risk: A Hybrid Machine Learning Approach," Mathematics, MDPI, vol. 10(17), pages 1-17, August.
    4. Maimuna Khatari & A. A. Zaidan & B. B. Zaidan & O. S. Albahri & M. A. Alsalem, 2019. "Multi-Criteria Evaluation and Benchmarking for Active Queue Management Methods: Open Issues, Challenges and Recommended Pathway Solutions," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(04), pages 1187-1242, July.
    5. Sharfah Ratibah Tuan Mat & Mohd Faizal Ab Razak & Mohd Nizam Mohmad Kahar & Juliza Mohamad Arif & Salwana Mohamad & Ahmad Firdaus, 2021. "Towards a systematic description of the field using bibliometric analysis: malware evolution," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 2013-2055, March.
    6. Mohammed Talal & A. H. Alamoodi & O. S. Albahri & A. S. Albahri & Dragan Pamucar, 2024. "Evaluation of remote sensing techniques-based water quality monitoring for sustainable hydrological applications: an integrated FWZIC-VIKOR modelling approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(8), pages 19685-19729, August.
    7. James, Ajith Tom & Kumar, Girish & Tayal, Pushpal & Chauhan, Ashwin & Wadhawa, Chirag & Panchal, Jasmin, 2022. "Analysis of human resource management challenges in implementation of industry 4.0 in Indian automobile industry," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    8. Andrea De Mauro & Marco Greco & Michele Grimaldi, 2019. "Understanding Big Data Through a Systematic Literature Review: The ITMI Model," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(04), pages 1433-1461, July.
    9. Zheng, Y.G. & Yu, J.L., 2022. "Stabilization of multi-rotation unstable periodic orbits through dynamic extended delayed feedback control," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    10. Mohammed Talal & A. A. Zaidan & B. B. Zaidan & O. S. Albahri & M. A. Alsalem & A. S. Albahri & A. H. Alamoodi & M. L. M. Kiah & F. M. Jumaah & Mussab Alaa, 2019. "Comprehensive review and analysis of anti-malware apps for smartphones," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 72(2), pages 285-337, October.
    11. Radhwan Sneesl & Yusmadi Yah Jusoh & Marzanah A. Jabar & Salfarina Abdullah & Umar Ali Bukar, 2022. "Factors Affecting the Adoption of IoT-Based Smart Campus: An Investigation Using Analytical Hierarchical Process (AHP)," Sustainability, MDPI, vol. 14(14), pages 1-21, July.
    12. Jafar Ababneh, 2020. "Influencing Performance Measurements through Varying Packet Capacities of Queue Nodes - DRED," Modern Applied Science, Canadian Center of Science and Education, vol. 14(4), pages 1-23, April.
    13. Z. K. Mohammed & A. A. Zaidan & H. B. Aris & Hassan A. Alsattar & Sarah Qahtan & Muhammet Deveci & Dursun Delen, 2024. "Bitcoin network-based anonymity and privacy model for metaverse implementation in Industry 5.0 using linear Diophantine fuzzy sets," Annals of Operations Research, Springer, vol. 342(2), pages 1193-1233, November.
    14. F. M. Jumaah & A. A. Zaidan & B. B. Zaidan & R. Bahbibi & M. Y. Qahtan & A. Sali, 2018. "Technique for order performance by similarity to ideal solution for solving complex situations in multi-criteria optimization of the tracking channels of GPS baseband telecommunication receivers," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 68(3), pages 425-443, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:telsys:v:77:y:2021:i:3:d:10.1007_s11235-021-00773-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.